Shared cM Project 2020 Analysis, Comparison & Handy Reference Charts

Recently, Blaine Bettinger published V4 of the Shared cM Project, and along with that, Jonny Perl at DNAPainter updated the associated interactive tool as well, including histograms. I wrote about that, here.

The goal of the shared cM project was and remains to document how much DNA can be expected to be shared by various individuals at specific relationship levels. This information allows matches to at least minimally “position” themselves in a general location their trees or conversely, to eliminate specific potential relationships.

Shared cM Project match data is gathered by testers submitting their match information through the submission portal, here.

When the Shared cM Project V3 was released in September 2017, I combined information from various sources and provided an analysis of that data, including the changes from the V2 release in 2016.

I’ve done the same thing this year, adding the new data to the previous release’s table.

Compiled Comparison Table

I initially compiled this table for myself, then decided to update it and share with my readers. This chart allows me to view various perspectives on shared data and relationships and in essence has all the data I might need, including multiple versions, in one place. Feel free to copy and save the table.

In the comparison table below, the relationship rows with data from various sources is shown as follows:

  • White – Shared cM Project 2016
  • Peach – Shared cM Project 2017
  • Purple – Shared cM Project 2020
  • Green – DNA Detectives chart

I don’t know if DNA Detectives still uses the “green chart” or if they have moved to the interactive DNAPainter tool. I’ve retained the numbers for historical reference regardless.

Additionally, in some places, you’ll see references to the “degree of relationship,” as in “third degree relatives always match each other.” I’ve included a “Degree of Relationship” column to the far right, but I don’t come across those “relationship degree” references often anymore either. However, it’s here for reference if you need it.

23andMe still gives relationships in percentages, so I’ve included the expected shared percent of DNA for each relationship and the actual shared range from the DNA Detectives Green Chart.

One column shows the expected shared cM amount, assuming that 50% of the DNA from each ancestor is passed on in each generation. Clearly, we know that inheritance doesn’t happen that cleanly because recombination is a random event and children do NOT inherit exactly half of each ancestor’s DNA carried by their parents, but the average should be someplace close to this number.

shared cm table 2020

click to open separately, then use your magnifier to enlarge

The first thing I noticed about V4 is that there is a LOT more data which means that the results are likely more accurate. V4 increased by 32K data points, or 147%. Bravo to everyone who participated, to Blaine for the analysis and to Jonny for automating the results at DNAPainter.

Methods

Blaine provided his white paper, here, which includes “everything you need to know” about the project, and I strongly encourage you to read it. Not only does this document explain the process and methods, it’s educational in its own right.

On the first page, Blaine discusses issues. Any time you are crowd sourcing information, you’re going to encounter challenges and errors. Blaine did remove any entries that were clearly problematic, plus an additional 1% of all entries for each category – .5% from each end meaning the largest and smallest entries. This was done in an attempt to remove the results most likely to be erroneous.

Known issues include:

  • Data entry errors – I refer to these as “clerical mutations,” but they happen and there is no way, unless the error is egregious, to know what is a typo and what is real. Obviously, a parent sharing only a 10 cM segment with a child is not possible, but other data entry errors are well within the realm of possible.
  • Incorrect relationships – Misreported or misunderstood relationships will skew the numbers. Relationships may be believed to be one type, but are actually something else. For example, a half vs full sibling, or a half vs full aunt or uncle.
  • Misunderstood Relationships – People sometimes become confused as to the difference between “half” and “removed” from time to time. I wrote a helpful article titled Quick Tip – Calculating Cousin Relationships Easily.
  • Endogamy – Endogamy occurs when a population intermarries within itself, meaning that the same ancestral DNA is present in many members of the community. This genetic result is that you may share more DNA with those cousins than you would otherwise share with cousins at the same distance without endogamy.
  • Pedigree Collapse – Pedigree collapse occurs when you find the same ancestors multiple times in your tree. The closer to current those ancestors appear, the more DNA you will potentially carry from those repeat ancestors. The difference between endogamy and pedigree collapse is that endogamy is a community event and pedigree collapse has only to do with your own tree. You might just have both, too.
  • Company Reporting Differences – Different companies report DNA in different ways in addition to having different matching thresholds. For example, Family Tree DNA includes in your match total all DNA to 1 cM that you share with a match over the matching threshold. Conversely, Ancestry has a lower matching threshold, but often strips out some matching DNA using Timber. 23andMe counts fully identical segments twice and reports the X chromosome in their totals. MyHeritage does not report the X chromosome. There is no “right” or “wrong,” or standardization, simply different approaches. Hopefully, the variances will be removed or smoothed in the averages.
  • Distant Cousin Relationships – While this isn’t really an issue, per se, it’s important to understand what is being reported beyond 2nd cousin relationships in that the only relationships used to calculate these averages is the DNA from people who DO share DNA with their more distant cousins. In other words, if you do NOT match your 3rd cousin, then your “0” shared DNA is not included in the average. Only those who do match have their matching amounts included. This means that the average is only the average of people who match, not the average of all 3rd cousins.

Challenges aside, the Shared cM Project provides genealogists with a wonderful opportunity to use the combined data of tens of thousands of relationships to estimate and better understand the relationship range of our matches.

The Shared cM Project in combination with DNAPainter provides us with a wonderful tool.

Histograms

When analyzing the data, one of the first things I noticed was a very unusual entry for parent/child relationships.

We all know that children each inherit exactly half of their parent’s DNA. We expect to find an amount in the ballpark of 3400, give or take a bit for normal variances like read errors or reporting differences.

Shared cM parent child.png

click to enlarge

I did not expect to see a minimum shared cM amount for a child/parent relationship at 2376, fully 1024 cM below expected value of 3400 cM. Put bluntly, that’s simply not possible. You cannot live without one third of one of your parent’s DNA. If this data is actually accurate from someone’s account, please contact me because I want to actually see this phenomenon.

I reached out to Blaine, knowing this result is not actually possible, wondering how this would ever get through the quality control cycle at any vendor.

After some discussion, here’s Blaine’s reply:

If you look at the histogram, you’ll see that those are most likely outliers. One of my lessons for the ScP (Shared cM Project) lately is that people shouldn’t be using the data without the histograms.

People get frustrated with this, but I can’t edit data without a basis even if I think it doesn’t make sense. I have to let the data itself decide what data to remove. So I removed 1% from each relationship, the lowest 0.5% and the highest 0.5%. I could have removed more, but based on the histograms, [removing] more appeared to be removing too much valid data. As people submit more parent/child relationships these outliers/incorrect submissions will be removed. But thankfully using the histograms makes it clear.

Indeed, if you look on page 23 on Blaine’s white paper, you’ll see the following histogram of parent/child relationships submitted.

shared cm histogram.png

click to enlarge

Keep in mind that Blaine already removed any obvious errors, plus 1% of the total from either end of the spectrum. In this case, he utilized 2412 submissions, so he would have removed about 24 entries that were even further out on the data spectrum.

On the chart above, we can see that a total of about 14 are still really questionable. It’s not until we get to 3300 that these entries seem feasible. My speculation is that these people meant to type 3400 instead of 2400, and so forth.

shared cm parent grid.png

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The great news is that Jonny Perl at DNAPainter included the histograms so you can judge for yourself if you are in the weeds on the outlier scale by clicking on the relationship.

shared cm parent submissions.png

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Other relationships, like this niece/nephew relationship fit the expected bell shaped curve very nicely.

shared cm niece.png

Of course, this means that if you match your niece or nephew at 900 cM instead of the range shown above, that person is probably not your full niece or nephew – a revelation that may be difficult because of the implications for you, your parent and sibling. This would suggest that your sibling is a half sibling, not a full sibling.

Entering specific amounts of shared DNA and outputting probabilities of specific relationships is where the power of DNAPainter enters the picture. Let’s enter 900 cM and see what happens.

shared cm half niece.png

That 900 cM match is likely your half niece or nephew. Of course, this example illustrates perfectly why some relationships are entered incorrectly – especially if you don’t know that your niece or nephew is a half niece or nephew – because your sibling is a half-sibling instead of a full sibling. Some people, even after receiving results don’t realize there is a discrepancy, either because their data is on the boundary, with various relationships being possible, or because they don’t understand or internalize the genetic message.

shared cm full siblings.png

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This phenomenon probably explains the low minimum value for full siblings, because many of those full siblings aren’t. Let’s enter 1613 and see what DNAPainter says.

shared cm half sibling.png

You’ll notice that DNAPainter shows the 1613 cM relationship as a half-sibling.

shared cm sibling.png

And the histogram indeed shows that 1613 would be the outlier. Being larger that 1600, it would appear in the 1700 category.

shared cm half vs full.png

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Accurately discerning close relationships is often incredibly important to testers. In the histogram chart above, you can see that the blue and orange histograms plotted on the same chart show that there is only a very small amount of overlap between the two histograms. This suggests that some people, those in the overlap range, who believe they are full siblings are in reality half-siblings, and possibly, a few in the reverse situation as well.

What Else is Noteworthy?

First, some relationships cannot be differentiated or sorted out by using the cM data or histogram charts alone.

shared cm half vs aunt.png

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For example, you cannot tell the difference between half-siblings and an aunt/uncle relationship. In order to make that determination, you would need to either test or compare to additional people or use other clues such as genealogical research or geographic proximity.

Second, the ranges of many relationships are wider than they were before. Often, we see the lows being lower and the highs being higher as a result of more data.

shared cm low high.png

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For example, take a look at grandparents. The expected relationship is 1700 cM, the average is 1754 which is very close to the previous average numbers of 1765 and 1766. However, the minimum is now 984 and the new maximum is 2462.

Why might this be? Are ranges actually wider?

Blaine removed 1% each time, which means that in V3, 6 results would have been removed, 3 from each end, while 11 would be removed in V4. More data means that we are likely to see more outliers as entries increase, with the relationship ranges are increasingly likely to overlap on the minimum and maximum ends.

Third, it’s worth noting that several relationships share an expected amount of DNA that is equal, 12.5% which equals 850 cM, in this example.

shared cm 4 relationships.png

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These four relationships appear to be exactly the same, genetically. The only way to tell which one of these relationships is accurate for a given match pair, aside from age (sometimes) and opportunity, is to look at another known relationship. For example, how closely might the tester be related to a parent, sibling, aunt, uncle or first cousin, or one of their other matches. Occasionally, an X chromosome match will be enlightening as well, given the unique inheritance path of the X chromosome.

Additional known relationships help narrow unknown relationships, as might Y DNA or mitochondrial DNA testing, if appropriate. You can read about who can test for the various kinds of tests, here.

Fourth, it’s been believed for several years that all 5th degree relatives, and above, match, and the V4 data confirms that.

shared cm 5th degree.png

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There are no zeroes in the column for minimum DNA shared, 4th column from right.

5th degree relatives include:

  • 2nd cousins
  • 1st cousins twice removed
  • Half first cousins once removed
  • Half great-aunt/uncle

Fifth, some of your more distant cousins won’t match you, beginning with 6th degree relationships.

shared cm disagree.png

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At the 6th degree level, the following relationships may share no DNA above the vendor matching threshold:

  • First cousins three times removed
  • Half first cousins twice removed
  • Half second cousins
  • Second cousins once removed

You’ll notice that the various reporting models and versions don’t always agree, with earlier versions of the Shared cM Project showing zeroes in the minimum amount of DNA shared.

Sixth, at the 7th degree level, some number of people in every relationship class don’t share DNA, as indicated by the zeros in the Shared cM Minimum column.

shared cm 7th degree.png

click to enlarge

The more generations back in time that you move, the fewer cousins can be expected to match.

shared cm isogg cousin match.png

This chart from the ISOGG Wiki Cousin statistics page shows the probability of matching a cousin at a specific level based on information provided by testing companies.

Quick Reference Chart Summary

In summary, V4 of the Shared cM Project confirms that all 2nd cousins can expect to match, but beyond that in your trees, cousins may or may not match. I suspect, without evidence, that the further back in time that people are related, the less likely that the proper “cousinship level” is reported. For example, it would be easier to confuse 7th and 8th cousins as compared to 1st and 2nd cousins. Some people also confuse 8th cousins with 8 generations back in your tree. It’s not equivalent.

shared cm eighth cousin.png

click to enlarge

It’s interesting to note that Degree 17 relatives, 8th cousins, 9 generations removed from each other (counting your parents as generation 1), still match in some cases. Note that some companies and people count you as generation 1, while others count your parents as generation 1.

The estimates of autosomal matching reaching 5 or 6 generations back in time, meaning descendants of common 4 times great-grandparents will sometimes match, is accurate as far as it goes, although 5-6 generations is certainly not a line in the sand.

It would be more accurate to state that:

  • 2nd cousins, people descended from common great-grandparents, 3 generations back in time will always match
  • 4th cousins, people descended from common 3 times great grandparents, 5 generations back in time, will match about half of the time
  • 8th cousins, people descended from 7 times great grandparents, 9 generations back in time still match a small percentage of the time
  • Cousins from more distant ancestors can possibly match, but it’s unlikely and may result from a more recent unknown ancestor

I created this summary chart, combining information from the ISOGG chart and the Shared cM Project as a handy quick reference. Enjoy!

shared cm quick reference.png

click to enlarge

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DNA Inherited from Grandparents and Great-Grandparents

Philip Gammon, our statistician friend has been working with crossover simulations again in order to tell us what we might expect relative to how much DNA we actually inherit from grandparents and great-grandparents.

We know that on average, we’re going to inherit 25% of our DNA from each grandparent – but we also know in reality that’s not what happens. We get more or less than exactly 25% from each person in a grandparent pair. It’s the total of the DNA of both grandparents that adds up to 50% for the couple.

How does this work, and does it make a difference whether we inherit our grandparent’s DNA through males or females?

Philip has answers for us as a result of his simulations.

DNA Inheritance from Grandparents

Philip Gammon:

When we consider the DNA that we inherit from our ancestors the only quantity that we can be certain of is that we receive half of our autosomal DNA from each parent. This is delivered to us in the form of the 22 segments (i.e. chromosomes) provided by our mothers in the ova and the 22 segments/chromosomes provided by our fathers in the sperm cell. Beyond parent-child relationships we tend to talk about averages. For instance, we receive an average of one quarter of our DNA from each of our four grandparents and an average of one-eighth of our DNA from each of our eight great-grandparents etc.

These figures vary because our parents didn’t necessarily pass on to us equal portions of the DNA that they received from their parents. The level of variation is driven by the number (and location) of crossover events that occur when the ova and the sperm cells are created.

The statistics relevant to the recombination process were discussed in detail in a previous article (Crossovers: Frequency and Inheritance Statistics – Male Versus Female Matters). With the availability these days of abundant real data from direct-to-consumer genetic testing companies (such as the 23andMe data utilised by Campbell et. al. in their paper titled “Escape from crossover interference increases with maternal age”) we can use this information as a basis for simulations that accurately mimic the crossover process. From these simulations we can measure the amount of variation that is expected to be observed in the proportions of DNA inherited from our ancestors. This is precisely what I have done in simulations run on my GAT-C model.

Before looking at the simulation results let’s anticipate what we expect to see. The previous article on crossover statistics revealed that there are an average of about 42 crossovers in female meiosis and about 27 in male meiosis. So, on the set of 22 chromosomes received from our mothers there will have been an average of 42 crossover locations where there was a switch between DNA she inherited from one parent to the other. That means that the DNA we inherit from our maternal grandparents typically comes in about 64 segments, but it won’t necessarily be 32 segments from each maternal grandparent. Chromosomes that experienced an odd number of crossovers contain an even number of segments (half originating from the grandmother, the other half from the grandfather) but chromosomes with an even number of crossovers (or zero!) have an odd number of segments so on these chromosomes you must receive one more segment from one grandparent than the other. And of course not all segments are the same size either. A single crossover occurring close to one end of the chromosome results in a small segment from one grandparent and a large segment from the other. All up there are quite a few sources of variation that can affect the amount of DNA inherited from grandparents. The only certainty here is that the amount inherited from the two maternal grandparents must add to 50%. If you inherit more than the average of 25% from one maternal grandparent that must be offset by inheriting less than 25% from the other maternal grandparent.

Gammon grandparents maternal percent.png

The above chart shows the results of 100,000 simulation runs. Excluding the bottom and top 1% of results, 98% of people will receive between 18.7% and 31.3% of their DNA from a maternal grandparent. The more darkly shaded region in the centre shows the people who receive a fairly even split of between 24% and 26% from the maternal grandparents. Only 28.8% of people are in this region and the remainder receive a less even contribution.

On the set of 22 chromosomes received from fathers there will have been an average of around 27 crossovers so the DNA received from the paternal grandparents has only been split into around 49 segments. It’s the same amount of DNA as received from mothers but just in larger chunks of the grandparent’s DNA. This creates greater opportunity for the father to pass on unequal amounts of DNA from the two grandparents so it would be expected that results from paternal inheritance will show more variation than from maternal inheritance.

Gammon grandparents paternal percent.png

The above chart shows the results of 100,000 simulated paternal inheritance events. They are more spread out than the maternal events with the middle 98% of people receiving between 16.7% and 33.3% of their DNA from a paternal grandparent. Only 21.9% of people receive a fairly even split of between 24% and 26% from each paternal grandparent as shown by the more darkly shaded region in the centre.

Gammon grandparents percent cM.png

To help with the comparison between maternal and paternal inheritance from grandparents the two distributions have been overlayed on the same scale in the chart above. And what are the chances of receiving a fairly even split of grandparents DNA from both your mother and your father? Only 6.3% of people can be expected to inherit an amount of between 24% and 26% of their DNA from all four grandparents.

Now I’ll extend the simulations out to the next generation and examine the variation in proportions of DNA inherited from the eight great-grandparents. There are effectively four groups of great-grandparents:

  • Mother’s maternal grandparents
  • Mother’s paternal grandparents
  • Father’s maternal grandparents
  • Father’s paternal grandparents

The DNA from group 1 has passed to you via two maternal recombination events, from your mother’s mother to your mother, then from your mother to you. On average there would have been 42 crossovers in each of these recombination events. Group 4 comprised two paternal recombination events averaging only 27 crossovers in each. The average amount of DNA received along each path is the same but along the group 1 path it would comprise of more numerous smaller segments than the group 4 path. Groups 2 and 3 would be somewhere between, both consisting of one maternal and one paternal recombination event.

Gammon greatgrandparents percent cM.png

The above chart shows the variation in the amount of DNA received from members of the four groups of great-grandparents. 25,000 simulations were performed. The average amount from any great-grandparent is 12.5% but there can be considerably more variation in the amount received from the father’s paternal grandparents than from the mother’s maternal grandparents. Groups 2 and 3 are between these two extremes and are equivalent. It doesn’t matter whether a paternal recombination follows a maternal one or vice versa – the end result is that both paths consist of the same average number of crossovers.

The table below shows the range in the amount of DNA that people receive from their great-grandparents. The bottom and top 1% of outcomes have been excluded. Note that these are based on a total of 3,418 cM for the 22 autosomes which is the length observed in the Campbell et. al. study. The average of 12.5% of total DNA is 854.5 cM:

Group 1st percentile 99th percentile
Mother’s maternal grandparents 522 cM 1219 cM
Mother’s paternal grandparents 475 cM 1282 cM
Father’s maternal grandparents 475 cM 1281 cM
Father’s paternal grandparents 426 cM 1349 cM

As a matter of interest, in each of the 25,000 simulations the amount of DNA received from the eight great-grandparents were sorted into order from the highest cM to the lowest cM. The averages of each of these eight amounts were then calculated and the results are below:

Gammon greatgrandparents average cM.png

On average, a person receives 1,129 cM from the great-grandparent that they inherited the most of their DNA from and only 600 cM from the great-grandparent that they received the least of their DNA from. But none of us are the result of 25,000 trials – we are each the product of recombination events that occurred once only. The above chart shows the average or typical variation in the amount of DNA received from the eight great-grandparents. Half of people will have experienced more variation than shown above and half of people will have experienced less variation.

Could you have received the same amount of DNA from all eight grandparents? Of course, it is possible, but it turns out that it is extremely unlikely. The average is 12.5% (854.5 cM) so anything between 12% (820.4 cM) and 13% (888.7 cM) could be considered as being close to this figure. The results reveal that this did not occur in any of the 25,000 simulations. Not one person received amounts between 12% and 13% from all eight great-grandparents.

Widening the criteria, I observe that there were 13 instances in the 25,000 simulations where people received between 11.5% and 13.5% of their DNA from all eight great-grandparents. That is still an extremely rare occurrence. Expanding the range further to between 11% and 14% saw a total of 126 instances, but this still only represents about half a percent of all observations. I think that we just have to face the fact that unless we are an extremely rare individual then we will not have inherited close to equal amounts of DNA from our eight great-grandparents.

Now, back to Roberta.

Thanks Philip.

Now we see why we might not inherit the same amount of DNA from our grandparents and great-grandparents.

We Don’t Have Equal Numbers of Matches on Tree Branches

This also might explain, at least in part, why people don’t have the same number of DNA matches on each branch of their tree.

Of course, other reasons include:

  • Uneven family sizes
  • Fewer or more cousins testing on different branches
  • Recent immigration meaning there are few people available to test
  • Family from a region where DNA testing and/or genealogy is not popular
  • Endogamy which dramatically increases the number of people you will match

Real Life Example

In our real-life example, two grandchildren are fortunate to have three grandparents and one great-grandparent available for matching.

For comparison purposes, let’s take a look at how many matches each grandchild has in common with their grandparents and great-grandparent.

The line of descent is as follows:

Gammon line of descent.png

Both end of line testers are female children.

The transmission path from their great-grandmother is:

  • Female to their paternal grandmother
  • Female to their father
  • Male to female tester

The transmission path from their maternal grandfather is:

  • Male to their mother
  • Female to female tester

The transmission path from their maternal grandmother is:

  • Female to their mother
  • Female to female tester

This first chart shows the number of common matches.

Matches Grand 1 Grand 2 GGF GGM Grand 3 Grand 4
Female 1 absent 1061 absent 238 529 1306
Female 2 absent 1225 absent 431 700 1064

It’s interesting that the matches in just 3 generations to the great-grandmother vary by 55%. The second tester has almost twice as many matches in common with her great-great-grandmother as she does the first tester. There a difference in the earlier generation, meaning matches to Grand 2, but only about 23%. That difference increased significantly in one generation.

The second chart shows the total number of matching cM with the matching family member.

Total cM Grand 1 Grand 2 GGF GGM Grand 3 Grand 4
Female 1 absent 1688 absent 713 1601 1818
Female 2 absent 1750 absent 852 1901 1511

We can see that the amount of DNA inherited from a grandparent does correlate with the number of matches to that grandparents. The more DNA shared, of course the better the chances of sharing that DNA with another person. However, multiple factors may be involved with why some people have more or fewer matches.

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Disclosure

I receive a small contribution when you click on some of the links to vendors in my articles. This does NOT increase the price you pay but helps me to keep the lights on and this informational blog free for everyone. Please click on the links in the articles or to the vendors below if you are purchasing products or DNA testing.

Thank you so much.

DNA Purchases and Free Transfers

Genealogy Products and Services

Genealogy Research

Fun DNA Stuff

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Are You DNA Testing the Right People?

We often want to purchase DNA kits for relatives, especially during the holidays when there are so many sales. (There are links for free shipping on tests in addition to sale prices at the end of this article. If you already know who to test, pop on down to the Sales section, now.)

Everyone is on a budget, so who should we test to obtain results that are relevant to our genealogy?

We tell people to test as many family members as possible – but what does that really mean?

Testing everyone may not be financially viable, nor necessary for genealogy, so let’s take a look at how to decide where to spend YOUR testing dollars to derive the most benefit.

It’s All Relative😊

When your ancestors had children, those children inherited different pieces of your ancestors’ DNA.

Therefore, it’s in your best interest to test all of the direct descendants generationally closest to the ancestor that you can find.

It’s especially useful to test descendants of your own close ancestors – great-great-grandparents or closer – where there is a significant possibility that you will match your cousins.

All second cousins match, and roughly 90% (or more) of third cousins match.

Percent of cousins match.png

This nifty chart compiled by ISOGG shows the probability statistics produced by the major testing companies regarding cousin matching relationships.

My policy is to test 4th cousins or closer. The more, the merrier.

Identifying Cousins

  • First cousins share grandparents.
  • Second cousins share great-grandparents.
  • Third cousins share great-great-grandparents.

The easiest way for me to see who these cousins might be is to open my genealogy software on my computer, select my great-great-grandparent, and click on descendants. Pretty much all software has a similar function.

The resulting list shows all of the descendants of that ancestor that I’ve entered in my software. Most genealogists already have or could construct this information with relative ease. These are the cousins you need to be talking to anyway, because they will have photos and stories that you don’t. If you don’t know them, there’s never been a better time to reach out and introduce yourself.

Who to test descendants software

Click to enlarge

People You Already Know

Sometimes it’s easier to start with the family you already know and may see from time to time. Those are the people who will likely be the most beneficial to your genealogy.

Who to test 1C.png

Checking my tree at FamilyTreeDNA, Hiram Ferverda and Evaline MIller are my great-grandparents. All of their children are deceased, but I have a relationship with the children born to their son, Roscoe. Both Cheryl and her brother carry parts of Hiram and Eva’s DNA their son John Ferverda (my grandfather) didn’t inherit, and therefore that I can’t carry.

Therefore, it’s in my best interest to gift my cousin, Cheryl and her brother, both, with DNA kits. Turns out that I already have and my common matches with both Cheryl and her brother are invaluable because I know that people who match me plus either one of them descend from the Ferverda or Miller lines. This relationship and linking them on my tree, shown above, allows Family Tree DNA to perform phased Family Matching which is their form of triangulation.

It’s important to test both siblings, because some people will match me plus one but not the other sibling.

Who’s Relevant?

Trying to convey the concept of who to test and not to test, and why, is sometimes confusing.

Many family members may want to test, but you may only be willing to pay for those tests that can help your own genealogy. We need to know who can best benefit our genealogy in order to make informed decisions.

Let’s look at example scenarios – two focused on grandparents and two on parents.

In our example family, a now-deceased grandmother and grandfather have 3 children and multiple grandchildren. Let’s look at when we test which people, and why.

Example 1: Grandparents – 2 children deceased, 1 living

In our first example, Jane and Barbara, my mother, are deceased, but their sibling Harold is living. Jane has a living daughter and my mother had 3 children, 2 of which are living. Who should we test to discover the most about my maternal grandparents?

Please note that before making this type of a decision, it’s important to state the goal, because the answer will be different depending on your goal at hand. If I wanted to learn about my father’s family, for example, instead of my maternal grandparents, this would be an entirely different question, answer, and tree.

Descendant test

Click to enlarge

The people who are “married in” but irrelevant to the analysis are greyed out. In this case, all of the spouses of Jane, Barbara and Harold are irrelevant to the grandmother and grandfather shown. We are not seeking information about those spouses or their families.

The people I’ve designated with the red stars should be tested. This is the “oldest” generation available. Harold can be tested, so his son, my first cousin, does not need to test because the only part of the grandparent’s DNA that Harold’s son can inherit is a portion of what his father, Harold, carries and gave to him.

Unfortunately, Jane is deceased but her daughter, Liz, is available to test, so Liz’s son does not need to.

I need to test, as does my living brother and the children of my deceased brother in order to recover as much as possible of my mother’s DNA. They will all carry pieces of her DNA that I don’t.

The children of anyone who has a red star do NOT need to test for our stated genealogical purpose because they only carry a portion of thier parent’s DNA, and that parent is already testing.

Those children may want to test for their own genealogy given that they also have a parent who is not relevant to the grandfather and grandmother shown. In my case, I’m perfectly happy to facilitate those tests, but not willing to pay for the children’s tests if the relevant parent is living. I’m only willing to pay for tests that are relevant to my genealogical goals – in this case, my grandparents’ heritage.

In this scenario, I’m providing 5 tests.

Of course, you may have other family factors in play that influence your decision about how many tests to purchase for whom. Family dynamics might include things like hurt feelings and living people who are unwilling or unable to test. I’ve been known to purchase kits for non-biologically related family members so that people could learn how DNA works.

Example 2: Grandparents – 2 children living, one deceased

For our second example, let’s change this scenario slightly.

Descendant test 2

Click to enlarge

From the perspective of only my grandparents’ genealogy, if my mother is alive, there’s no reason to test her children.

Barbara and Harold can test. Since Jane is deceased, and she had only one child, Liz is the closest generationally and can test to represent Jane’s line. Liz’s son does not need to test since his mother, the closest relative generationally to the grandparents is available to test.

In this scenario, I’m providing 3 tests.

Example 3: My Immediate Family – both parents living

In this third example, I’m looking from strictly MY perspective viewing my maternal grandparents (as shown above) AND my immediate family meaning the genealogical lines of both of my parents. In other words, I’ve combined two goals. This makes sense, especially if I’m going to be seeing a group of people at a family gathering. We can have a swab party!

Descendants - parents alive

Click to enlarge

In the situation where my parents are both living, I’m going to test them in addition to Harold and Liz.

I’m testing myself because I want to work using my own DNA, but that’s not really necessary. My parents will both have twice as many matches to other people as I do – because I only inherited half of each parent’s DNA.

In this scenario, I’m providing 5 tests.

Example 4: My Immediate Family – one parent living, one deceased

Descendants - father deceased

Click to enlarge

In our last example, my mother is living but my father is deceased. In addition to Harold and Liz who reflect the DNA of my maternal grandparents, I will test myself, my mother my living brother and my deceased brother’s child.

Because my father is deceased, testing as many of my father’s descendants as possible, in addition to myself, is the only way for me to obtain some portion of his DNA. My siblings will have pieces of my parent’s DNA that I don’t.

I’m not showing my father’s tree in this view, but looking at his tree and who is available to test to provide information about his side of the family would be the next logical step. He may have siblings and cousins that are every bit as valuable as the people on my mother’s side.

Applying this methodology to your own family, who is available to test?

Multiple Databases

Now that you know WHO to test, the next step is to make sure your close family members test at each of the major providers where your DNA is as well.

I test everyone at Family Tree DNA because I have been testing family members there for 19 years and many of the original testers are deceased now. The only way new people can compare to those people is to be in the FamilyTreeDNA data base.

Then, with permission of course, I transfer all kits, for free, to MyHeritage. Matching is free, but if you don’t have a subscription, there’s an unlock fee of $29 to access advanced tools. I have a full subscription, so all tools are entirely free for the kits I transfer and manage in my account.

Transferring to Family Tree DNA and matching there is free too. There’s an unlock fee of $19 for advanced tools, but that’s a good deal because it’s substantially less than a new test.

Neither 23andMe nor Ancestry accept transfers, so you have to test at each of those companies.

The great news is that both Ancestry and 23andMe tests can be transferred to  MyHeritage and FamilyTreeDNA.

Before purchasing tests, check first by asking your relatives or testing there yourself to be sure they aren’t already in those databases. If they took a “spit in a vial” test, they are either at 23andMe or Ancestry. If they took a swab test, it’s MyHeritage or FamilyTreeDNA.

I wrote about creating a testing and transfer strategy in the article, DNA Testing and Transfers – What’s Your Strategy? That article includes a handy dandy chart about who accepts which versions of whose files.

Sales

Of course, everything is on sale since it’s the holidays.

Who are you planning to test?

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